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The arrival of Artificial Intelligence (AI) in medicine has represented a true revolution, and in just a year, the first clinical trials with drugs developed using this technology are expected to begin.
According to Nobel Prize-winning chemist Demis Hassabis, the positive impact of AI will transform the treatments for all diseases, including oncological, neurodegenerative, and cardiovascular diseases.
Hassabis received the Nobel Prize in October alongside two colleagues for the development of an AI tool named AlphaFold AI, which predicts the three-dimensional structures of proteins.
The expert exemplified how his creation could help millions of people around the world. He recalled that one of the hypotheses regarding the causes of Alzheimer's is that certain proteins, the beta-amyloids, fold incorrectly and then group around the neurons, ultimately killing them.
"AlphaFold can predict what the correct structure should be and, potentially, what happens when it goes wrong. If you have the 3D structure of the protein, you can design pharmacological compounds, which are chemical compounds that bind to the right part of the protein," he explained at the annual meeting of the World Economic Forum (WEF) in Davos.
Hassabis explained that proteins are usually sequenced genetically but in a one-dimensional chain. The challenge is to see the structure in three dimensions (3D), "because the 3D structure tells you what the protein does, how it reacts," he noted.
The problem is that a protein can adopt countless spatial configurations, and this is where artificial intelligence comes into play, enabling an intelligent search.
In the human body, proteins fold correctly in a minimal time (only in certain configurations) to perform the functions for which they are programmed. "And it turns out that we can imitate that physical process, with AI and AlphaFold," emphasized the scientist, cited by EFE.
Frequently Asked Questions About the Medical Revolution with AI and Its Impact
How is Artificial Intelligence revolutionizing drug development?
Artificial Intelligence, through tools like AlphaFold AI, is revolutionizing drug development by predicting the three-dimensional structures of proteins. This allows for the design of more effective pharmacological compounds to treat various diseases, including oncological, neurodegenerative, and cardiovascular conditions. This capability of AI promises to transform disease treatment by facilitating the design of specific medications that interact with the correct parts of proteins.
When will clinical trials of drugs developed with AI begin?
Clinical trials for drugs developed with Artificial Intelligence are expected to begin in about a year. This advancement marks a significant milestone in the use of AI for medicine, allowing for the testing of new therapies based on the detailed knowledge of protein structures predicted by AI.
How could AlphaFold AI assist in the treatment of Alzheimer's?
AlphaFold AI can assist in the treatment of Alzheimer's by predicting the correct structure of beta-amyloid proteins, which misfold and cluster around neurons. Knowing the 3D structure, it is possible to design compounds that prevent the aggregation of these proteins and potentially slow down the progression of the disease.
What challenges does Cuba face in implementing AI in its healthcare system?
Cuba faces significant challenges in implementing AI in its healthcare system due to its outdated digital infrastructure, constant power outages, and limited internet access. These structural limitations hinder the effective development and application of cutting-edge technologies like AI, despite the Cuban government's desire to advance in this field.
What role does ethics play in the development of drugs with AI?
Ethics plays a crucial role in the development of AI medications, as it ensures that these technologies are applied responsibly and safely. It is essential to guarantee transparency, fairness, and the protection of personal data in the use of AI so that benefits are distributed equitably and potential risks are minimized.
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